MAS-YOLOv11: An Improved Underwater Object Detection Algorithm Based on YOLOv11 by Yang Luo, Aiping Wu, Qingqing Fu

“…Third, we introduce a Slide Loss function with dynamic sample weighting to enhance hard sample learning. …”
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An Intermittent Fertilization Control System for Fruit Tree Crown Detection by Hao Yin, Pengyu Jing, Chen Ma, Liewang Cao, Chengsong Li, Lihong Wang

“…The mean effective fertilization rate exceeded 85%, with the primary indices satisfying the agronomic criteria.…”
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TrainNet for locking state recognition of side door of railway freight car by Ning Xing, Cai Kangcheng, Zhou Shumin, Lan Xiangui, Lai Yihui

“…An LSKCSPC module is also introduced to capture a dynamic receptive field, enabling TrainNet to adjust its receptive field dynamically to the scale of the object, improving its feature representation capacity. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…However, due to the influence of multiple factors such as supply-demand dynamics, seasonality, and weather conditions, agricultural product prices exhibit highly nonlinear and dynamic characteristics, making traditional methods often insufficient for accurate price change prediction. …”
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DS-YOLO: A dense small object detection algorithm based on inverted bottleneck and multi-scale fusion network by Hongyu Zhang, Guoliang Li, Dapeng Wan, Ziyue Wang, Jinshun Dong, Shoujun Lin, Lixia Deng, Haiying Liu

“…Finally, to minimize feature loss of dense objects during network transmission, a dynamic upsampling module, DySample, is implemented. …”
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High-Precision Complex Orchard Passion Fruit Detection Using the PHD-YOLO Model Improved from YOLOv11n by Rongxiang Luo, Rongrui Zhao, Xue Ding, Shuangyun Peng, Fapeng Cai

“…The integration of the HSV Attentional Fusion (HSVAF) module within the backbone network facilitates the fusion of HSV color space characteristics with an adaptive attention mechanism, thereby enhancing feature discriminability under dynamic lighting conditions. …”
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Electrophysical Treatment Device for Enhancing the Storage Performance of Potatoes and Vegetable Crops by N. V. Sazonov, A. V. Sibirev, M. A. Mosyakov, M. S. Trunov, A. О. Volkov, D. D. Kondrakhov

“…The automated process control system integrated with an orienting module must ensure the following: adjustment and maintenance of the translational speed of treated products; dynamic modification of the electrophysical treatment mode based on the actual feed rate; the physical and mechanical properties of the bulk material; the technological parameters of tubers; and the operation of the orienting module. …”
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Encrypted traffic identification method based on deep residual capsule network with attention mechanism by Guozhen SHI, Kunyang LI, Yao LIU, Yongjian YANG

“…With the improvement of users’ security awareness and the development of encryption technology, encrypted traffic has become an important part of network traffic, and identifying encrypted traffic has become an important part of network traffic supervision.The encrypted traffic identification method based on the traditional deep learning model has problems such as poor effect and long model training time.To address these problems, the encrypted traffic identification method based on a deep residual capsule network (DRCN) was proposed.However, the original capsule network was stacked in the form of full connection, which lead to a small model coupling coefficient and it was impossible to build a deep network model.The DRCN model adopted the dynamic routing algorithm based on the three-dimensional convolutional algorithm (3DCNN) instead of the fully-connected dynamic routing algorithm, to reduce the parameters passed between each capsule layer, decrease the complexity of operations, and then build the deep capsule network to improve the accuracy and efficiency of recognition.The channel attention mechanism was introduced to assign different weights to different features, and then the influence of useless features on the recognition results was reduced.The introduction of the residual network into the capsule network layer and the construction of the residual capsule network module alleviated the gradient disappearance problem of the deep capsule network.In terms of data pre-processing, the first 784byte of the intercepted packets was converted into images as input of the DRCN model, to avoid manual feature extraction and reduce the labor cost of encrypted traffic recognition.The experimental results on the ISCXVPN2016 dataset show that the accuracy of the DRCN model is improved by 5.54% and the training time of the model is reduced by 232s compared with the BLSTM model with the best performance.In addition, the accuracy of the DRCN model reaches 94.3% on the small dataset.The above experimental results prove that the proposed recognition scheme has high recognition rate, good performance and applicability.…”
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EER-DETR: An Improved Method for Detecting Defects on the Surface of Solar Panels Based on RT-DETR by Jiajun Dun, Hai Yang, Shixin Yuan, Ying Tang

“…In response to the shortcomings of existing detection methods in identifying tiny defects and model efficiency, this study innovatively constructed the EER-DETR detection framework: firstly, a feature reconstruction module WDBB with a differentiable branch structure was introduced to significantly enhance the feature retention ability for fine cracks and other small targets; secondly, an adaptive feature pyramid network EHFPN was innovatively designed, which achieved efficient integration of multi-level features through a dynamic weight allocation mechanism, reducing the model complexity by 9.7% while maintaining detection accuracy, solving the industry problem of “precision—efficiency imbalance” in traditional feature pyramid networks; finally, an enhanced upsampling component was introduced to effectively address the problem of detail loss that occurs in traditional methods during image resolution enhancement. …”
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Representation Enhancement-Based Proximal Policy Optimization for UAV Path Planning and Obstacle Avoidance by Xiangxiang Huang, Wei Wang, Zhaokang Ji, Bin Cheng

“…The representation enhancement (RE) module consists of observation memory improvement (OMI) and dynamic relative position-attitude reshaping (DRPAR). …”
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DCS-YOLOv5s: A Lightweight Algorithm for Multi-Target Recognition of Potato Seed Potatoes Based on YOLOv5s by Zhaomei Qiu, Weili Wang, Xin Jin, Fei Wang, Zhitao He, Jiangtao Ji, Shanshan Jin

“…The detection velocity has also been augmented by 12.07%, achieving a rate of 65 FPS. The DCS-YOLOv5s target detection model, by attaining model compactness, has substantially heightened the detection precision, presenting a beneficial reference for dynamic sample target detection in the context of potato-cutting machinery.…”
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Near-Infrared Hyperspectral Target Tracking Based on Background Information and Spectral Position Prediction by Li Wu, Mengyuan Wang, Weixiang Zhong, Kunpeng Huang, Wenhao Jiang, Jia Li, Dong Zhao

“…First, the history frame background information extraction module is proposed. This module performs spectral matching on the history frame images through the average spectral curve of the groundtruth value of the target and makes a rough distinction between the target and the background. …”
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IMPROVEMENT OF BUS OPERATIONAL CHARACTERISTICS WHILE USING INTEGRATED CONTROL OF SUSPENSION AND TRANSMISSION by V. V. Mikhailau, A. G. Snitkov, S. V. Liahov

“…The developed algorithm and stabilization system according to angular rate of body’s center line turning have made it possible to improve dynamics of the bus while making gear-changing and to reduce fuel consumption during starting-up and speed picking-up processes. …”
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Behavior Analysis of Students in Preschool Mathematics Teaching Based on Deep Learning by Guangning Qin

“…Combining the channel attention mechanism with deep convolution, a dynamic channel attention convolution (DCAConv) is proposed, which can dynamically adjust the channel weights and capture key features more sensitively. …”
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Vision-Guided Maritime UAV Rescue System with Optimized GPS Path Planning and Dual-Target Tracking by Suli Wang, Yang Zhao, Chang Zhou, Xiaodong Ma, Zijun Jiao, Zesheng Zhou, Xiaolu Liu, Tianhai Peng, Changxing Shao

“…Furthermore, a dual-target-tracking algorithm—integrating motion prediction with color-based landing zone recognition—achieves a 96% success rate in precision landings under dynamic conditions. …”
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A lightweight trichosanthes kirilowii maxim detection algorithm in complex mountain environments based on improved YOLOv7-tiny. by Zhongjian Xie, Xinwei Chen, Weilin Wu, Yao Xiao, Yuanhang Li, Yaya Zhang, ZhuXuan Wan, Weiqi Chen

“…Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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Remote Sensing Image Compression via Wavelet-Guided Local Structure Decoupling and Channel–Spatial State Modeling by Jiahui Liu, Lili Zhang, Xianjun Wang

“…It comprises two key modules. The Wavelet Transform-guided Local Structure Decoupling (WTLS) module applies multi-scale wavelet decomposition to disentangle and separately encode low- and high-frequency components, enabling efficient parallel modeling of global contours and local textures. …”
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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

“…However, the existing methods had poor robustness; they not only had high error rate of target recognition but also had high dependence on parameters, so they were limited in application. …”
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A Nutritional Bioenergetic Model for Farmed Fish: Effects of Food Composition on Growth, Oxygen Consumption and Waste Production by Orestis Stavrakidis-Zachou, Ep H. Eding, Nikos Papandroulakis, Konstadia Lika

“…The proposed nutritional bioenergetics model is based on the dynamic energy budget (DEB) theory, a mechanistic framework to study individual metabolism. …”
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Enhancing Recommendation Systems with Real-Time Adaptive Learning and Multi-Domain Knowledge Graphs by Zeinab Shahbazi, Rezvan Jalali, Zahra Shahbazi

“…However, existing models still struggle to adapt dynamically to users’ evolving interests across multiple content domains in real-time. …”
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